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Time-Domain Beamforming and Blind Source Separation : Speech Input in Car Env...
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A book in excellent condition. Cover is shiny and undamaged, and the dust jacket is included for hard covers. No missing or damaged pages, no creases or tears, and no underlining/highlighting of text or writing in the margins. May be very minimal identifying marks on the inside cover. Very minimal wear and tear.
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Item specifics
- Condition
- Book Title
- Time-Domain Beamforming and Blind Source Separation : Speech Inpu
- ISBN
- 9780387688350
- Subject Area
- Computers, Technology & Engineering, Science
- Publication Name
- Time-Domain Beamforming and Blind Source Separation : Speech Input in the Car Environment
- Publisher
- Springer
- Item Length
- 9.3 in
- Subject
- Mobile & Wireless Communications, Signals & Signal Processing, Telecommunications, Speech & Audio Processing, Acoustics & Sound
- Publication Year
- 2009
- Series
- Lecture Notes in Electrical Engineering Ser.
- Type
- Textbook
- Format
- Hardcover
- Language
- English
- Item Height
- 0.2 in
- Item Weight
- 40.2 Oz
- Item Width
- 6.1 in
- Number of Pages
- Xii, 225 Pages
About this product
Product Identifiers
Publisher
Springer
ISBN-10
0387688358
ISBN-13
9780387688350
eBay Product ID (ePID)
57119409
Product Key Features
Number of Pages
Xii, 225 Pages
Language
English
Publication Name
Time-Domain Beamforming and Blind Source Separation : Speech Input in the Car Environment
Publication Year
2009
Subject
Mobile & Wireless Communications, Signals & Signal Processing, Telecommunications, Speech & Audio Processing, Acoustics & Sound
Type
Textbook
Subject Area
Computers, Technology & Engineering, Science
Series
Lecture Notes in Electrical Engineering Ser.
Format
Hardcover
Dimensions
Item Height
0.2 in
Item Weight
40.2 Oz
Item Length
9.3 in
Item Width
6.1 in
Additional Product Features
Intended Audience
Scholarly & Professional
Dewey Edition
22
Series Volume Number
3
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
621.3845
Table Of Content
Account for Random Microstructure in Multiscale Models.- Multiscale Modeling of Tensile Failure in Fiber-Reinforced Composites.- Adaptive Concurrent Multi-Level Model for Multiscale Analysis of Composite Materials Including Damage.- Multiscale and Multi-Level Modeling of Composites.- A Micro-Mechanics-Based Notion of Stress for use in the Determination of Continuum-Level Mechanical Properties via Molecular Dynamics.- Multiscale Modeling and Simulation of Deformation in Nanoscale Metallic Multilayered Composites.- Multiscale Modeling of Composites Using Analytical Methods.- Nested Nonlinear Multiscale Frameworks for the Analysis of Thick-Section Composite Materials and Sructures.- Predicting Thermooxidative Degradation and Performance of High-Temperature Polymer Matrix Composites.- Modeling of Stiffness, Strength, and Structure-Property Relationship in Crosslinked Silica Aerogel.- Multiscale Modeling of the Evolution of Damage in Heterogeneous Viscoelastic Solids.- Multiscale Modeling for Damage Analysis.- Hierarchical Modeling of Deformation of Materials from the Atomic to the Continuum Scale.
Synopsis
Time-domain Beamforming and Convolutive Blind Source Separation addresses the problem of separating spontaneous multi-party speech by way of microphone arrays (beamformers) and adaptive signal processing techniques. While existing techniques requires a Double-Talk Detector (DTD) that interrupts the adaptation when the target is active, the described method addresses the separation problem using continuous, uninterrupted adaptive algorithms. The advantage of such an approach is twofold: Firstly, the algorithm development is much simpler since no detection mechanism needs to be designed and no threshold to be tuned. Secondly, the performance can be improved due to the adaptation during periods of double-talk., This book addresses the problem of separating spontaneous multi-party speech by way of microphone arrays (beamformers) and adaptive signal processing techniques. It is written is a concise manner and an effort has been made such that all presented algorithms can be straightforwardly implemented by the reader. All experimental results have been obtained with real in-car microphone recordings involving simultaneous speech of the driver and the co-driver., The development of computer and telecommunication technologies led to a revolutioninthewaythatpeopleworkandcommunicatewitheachother.One of the results is that large amount of information will increasingly be held in a form that is natural for users, as speech in natural language. In the presented work, we investigate the speech signal capture problem, which includes the separation of multiple interfering speakers using microphone arrays. Adaptive beamforming is a classical approach which has been developed since the seventies. However it requires a double-talk detector (DTD) that interrupts the adaptation when the target is active, since otherwise target cancelation occurs. The fact that several speakers may be active simulta- ouslymakesthisdetectiondi'cult,andifadditionalbackgroundnoiseoccurs, even less reliable. Our proposed approaches address this separation problem using continuous, uninterrupted adaptive algorithms. The advantage seems twofold:Firstly,thealgorithmdevelopmentismuchsimplersincenodetection mechanism needs to be designed and no threshold is to be tuned. Secondly, the performance may be improved due to the adaptation during periods of double-talk. In the ?rst part of the book, we investigate a modi'cation of the widely usedNLMSalgorithm,termedImplicitLMS(ILMS),whichimplicitlyincludes an adaptation control and does not require any threshold. Experimental ev- uations reveal that ILMS mitigates the target signal cancelation substantially with the distributed microphone array. However, in the more di'cult case of the compact microphone array, this algorithm does not su'ciently reduce the target signal cancelation. In this case, more sophisticated blind source se- ration techniques (BSS) seem necessary., The development of computer and telecommunication technologies led to a revolutioninthewaythatpeopleworkandcommunicatewitheachother.One of the results is that large amount of information will increasingly be held in a form that is natural for users, as speech in natural language. In the presented work, we investigate the speech signal capture problem, which includes the separation of multiple interfering speakers using microphone arrays. Adaptive beamforming is a classical approach which has been developed since the seventies. However it requires a double-talk detector (DTD) that interrupts the adaptation when the target is active, since otherwise target cancelation occurs. The fact that several speakers may be active simulta- ouslymakesthisdetectiondi'cult, andifadditionalbackgroundnoiseoccurs, even less reliable. Our proposed approaches address this separation problem using continuous, uninterrupted adaptive algorithms. The advantage seems twofold: Firstly, thealgorithmdevelopmentismuchsimplersincenodetection mechanism needs to be designed and no threshold is to be tuned. Secondly, the performance may be improved due to the adaptation during periods of double-talk. In the ?rst part of the book, we investigate a modi'cation of the widely usedNLMSalgorithm, termedImplicitLMS(ILMS), whichimplicitlyincludes an adaptation control and does not require any threshold. Experimental ev- uations reveal that ILMS mitigates the target signal cancelation substantially with the distributed microphone array. However, in the more di'cult case of the compact microphone array, this algorithm does not su'ciently reduce the target signal cancelation. In this case, more sophisticated blind source se- ration techniques (BSS) seem neces, The development of computer and telecommunication technologies led to a revolutioninthewaythatpeopleworkandcommunicatewitheachother.One of the results is that large amount of information will increasingly be held in a form that is natural for users, as speech in natural language. In the presented work, we investigate the speech signal capture problem, which includes the separation of multiple interfering speakers using microphone arrays. Adaptive beamforming is a classical approach which has been developed since the seventies. However it requires a double-talk detector (DTD) that interrupts the adaptation when the target is active, since otherwise target cancelation occurs. The fact that several speakers may be active simulta- ouslymakesthisdetectiondi?cult,andifadditionalbackgroundnoiseoccurs, even less reliable. Our proposed approaches address this separation problem using continuous, uninterrupted adaptive algorithms. The advantage seems twofold:Firstly,thealgorithmdevelopmentismuchsimplersincenodetection mechanism needs to be designed and no threshold is to be tuned. Secondly, the performance may be improved due to the adaptation during periods of double-talk. In the ?rst part of the book, we investigate a modi?cation of the widely usedNLMSalgorithm,termedImplicitLMS(ILMS),whichimplicitlyincludes an adaptation control and does not require any threshold. Experimental ev- uations reveal that ILMS mitigates the target signal cancelation substantially with the distributed microphone array. However, in the more di?cult case of the compact microphone array, this algorithm does not su?ciently reduce the target signal cancelation. In this case, more sophisticated blind source se- ration techniques (BSS) seem necessary.
LC Classification Number
TK5102.9
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